This paper describes a novel approach for obtaining semantic interoperability among data sources in a bottom-up, semiautomatic manner without relying on pre-existing, global seman...
Karl Aberer, Manfred Hauswirth, Philippe Cudr&eacu...
This paper discusses a novel distributed adaptive algorithm and representation used to construct populations of adaptive Web agents. These InfoSpiders browse networked information ...
Abstract. Most of the work in machine learning assume that examples are generated at random according to some stationary probability distribution. In this work we study the problem...
Although memory-based classifiers offer robust classification performance, their widespread usage on embedded devices is hindered due to the device's limited memory resources...
Graphical models are usually learned without regard to the cost of doing inference with them. As a result, even if a good model is learned, it may perform poorly at prediction, be...